openvinotoolkit / openvinotoolkit/nncf
[Good First Issue][NNCF]: Support not transposed weight for data-aware weight compression methods
@yuanjua is already working on this.
Since May 15, 2025.
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Description
Context
Matmul operation in OpenVINO assumes an implicit shape alignment for input arguments. It applies transpositions specified by optional transpose_a and transpose_b attributes: OV spec.
Currently, weight compression in NNCF does not support transpose_b=False.
Here's the test.
Potentially, it affects Mixed-Precision, AWQ, Scale Estimation, GPTQ and Lora Correction algorithms.
What needs to be done?
The task is to enable data-aware weight compression methods (Mixed-Precision, AWQ, Scale Estimation, Lora Correction, GPTQ) for models with matrix multiplications having not transposed weight.
test_compression_with_transpose shouldn't raise an error for transpose_b=False
Example Pull Requests
https://github.com/openvinotoolkit/nncf/issues/3230
https://github.com/openvinotoolkit/nncf/pull/3296
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Contact points
@ljaljushkin
Ticket
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